I believe the whole thing can be done in 0.3 seconds with the following approach: (Describing only the 'happy path' here - other paths can be made fast too, but will require different implementations) * Since temperatures are only to 0.1 decimal points, we have a finite number of temperatures. ~400 temperatures will cover all common cases. * We also have a finite number of place names. (~400) * Just make a lookup tab…
You don't need the look up table. All you are asked for is min/mean/max which can all be computed in one pass without storing the data. All you need is a hash table with 400 entries and 3 floats (running min, mean and max) and and int (count, for updating running mean). That's just 16 bytes, if you use 16 bytes for name of station you can fit everything under 16K. IO will dominate the running time for this, and JSON…
I always worried it was too easy, but I'm heartened by how many comments miss the insight I always looked for and you named: you don't need to store a single thing.
I do wonder if it'll work here, at least as simply as the tracking vars you mention, with so many rows, and the implicit spirit of "you should be able to handle _all_ data", overflow might become a legitimate concern - ex. we might not be able to track mean as simply as maintaining sum + count vars.
* "oh sorry times up, but the right answer is a red black self balancing terenary tree recursive breadth-first search", ironically, was one of my Apple interviews.